Data import and tables
## Loading BG.library
## Adding files missing in collate: addBGpoints.R, addBGpoints_ly.R, addBolusPoints_ly.R, addFasting_ly.R, addPercentBG_ly.R, addPumpSetting_ly.R, addStackbar_ly.R, barSubPlot_ly.R, boxPlot.R, dataImport.R, findCodeStr.R, heatMap.R, makeLayout.R, makeXaxis.R, makeYaxes - Copy.R, makeYaxes.R, makeYaxesBar.R, makeYaxesSetting.R, makeYdomain.R, plotLine_ly.R, setTimeStep.R, subsetData.R, summaryPlot_ly.R, timeDayTable.R, uniqueDateTime.R, xTicks.R
BGvalue_Summary
## time3 min mean max sd
## 1 00:00 114 114.00000 114 NaN
## 2 01:00 114 114.00000 114 NaN
## 3 02:00 Inf NaN -Inf NaN
## 4 03:00 Inf NaN -Inf NaN
## 5 04:00 Inf NaN -Inf NaN
## 6 05:00 Inf NaN -Inf NaN
## 7 06:00 236 260.66667 273 19.10672
## 8 07:00 115 132.00000 166 26.33629
## 9 08:00 73 73.00000 73 0.00000
## 10 09:00 Inf NaN -Inf NaN
## 11 10:00 189 189.00000 189 0.00000
## 12 11:00 Inf NaN -Inf NaN
## 13 12:00 60 218.88889 274 90.42462
## 14 13:00 Inf NaN -Inf NaN
## 15 14:00 153 221.57143 313 85.52360
## 16 15:00 181 181.00000 181 0.00000
## 17 16:00 66 87.00000 102 13.54991
## 18 17:00 66 86.00000 95 11.91638
## 19 18:00 61 61.00000 61 0.00000
## 20 19:00 Inf NaN -Inf NaN
## 21 20:00 132 236.66667 289 81.07445
## 22 21:00 63 94.33333 110 24.27070
## 23 22:00 Inf NaN -Inf NaN
## 24 23:00 172 172.00000 172 0.00000
## 25 00:00 156 156.00000 156 0.00000
Sensorvalue_Summary
## time3 min mean max sd
## 1 00:00 81 124.83333 184 33.10811
## 2 01:00 78 137.50000 229 52.87695
## 3 02:00 80 145.44444 239 57.78751
## 4 03:00 92 150.69444 197 33.68834
## 5 04:00 133 160.19444 199 14.32444
## 6 05:00 131 164.25000 215 33.03797
## 7 06:00 115 171.91667 269 52.91685
## 8 07:00 98 151.47222 270 53.93514
## 9 08:00 40 117.66667 235 70.12764
## 10 09:00 41 134.75000 246 74.08234
## 11 10:00 129 193.21622 266 35.90043
## 12 11:00 102 200.95833 272 61.38957
## 13 12:00 40 165.35417 309 103.96306
## 14 13:00 43 174.59459 279 69.50998
## 15 14:00 150 221.79412 311 56.86229
## 16 15:00 109 180.25000 290 50.48925
## 17 16:00 48 87.05556 139 25.84785
## 18 17:00 43 69.55556 130 20.96452
## 19 18:00 84 134.52778 172 23.91232
## 20 19:00 73 135.13889 190 29.58200
## 21 20:00 75 156.76923 287 68.21694
## 22 21:00 67 137.88889 276 64.70053
## 23 22:00 77 128.33333 186 33.57380
## 24 23:00 109 137.69444 181 17.98701
## 25 00:00 113 137.27778 183 28.87866
BGHigh_Count
## time3 BG.Reading..mg.dL.
## 1 06:00 6
## 2 07:00 2
## 3 10:00 4
## 4 12:00 7
## 5 14:00 7
## 6 15:00 2
## 7 20:00 4
## 8 23:00 4
## 9 00:00 2
BGveryHigh_Count
## time3 BG.Reading..mg.dL.
## 1 14:00 3
BGLow_Count
## time3 BG.Reading..mg.dL.
## 1 08:00 4
## 2 12:00 2
## 3 16:00 1
## 4 17:00 3
## 5 18:00 2
## 6 21:00 2
BGgood_Count
## time3 BG.Reading..mg.dL.
## 1 00:00 1
## 2 01:00 1
## 3 07:00 4
## 4 16:00 5
## 5 17:00 4
## 6 20:00 2
## 7 21:00 4
tempBasal_count
## time3 Temp.Basal.Amount
## 1 14:00 1
suspendBasal_Count
## time3 Alarm
## 1 00:00 2
## 2 01:00 2
## 3 07:00 1
## 4 08:00 4
## 5 09:00 1
## 6 12:00 6
## 7 16:00 6
## 8 17:00 8
## 9 18:00 1
## 10 19:00 1
## 11 20:00 1
## 12 21:00 1
BGvalue_timeDaytable
## time 2019-09-25 2019-09-26 2019-09-27 2019-09-28 2019-09-29 mean
## 1 00:00 NaN NaN 156.0000 114.00000 NaN 135.00000
## 2 01:00 NaN NaN NaN 114.00000 NaN 114.00000
## 3 02:00 NaN NaN NaN NaN NaN NaN
## 4 03:00 NaN NaN NaN NaN NaN NaN
## 5 04:00 NaN NaN NaN NaN NaN NaN
## 6 05:00 NaN NaN NaN NaN NaN NaN
## 7 06:00 NaN NaN 236.0000 273.00000 NaN 254.50000
## 8 07:00 NaN 115.0 166.0000 NaN NaN 140.50000
## 9 08:00 73.00 NaN NaN NaN NaN 73.00000
## 10 09:00 NaN NaN NaN NaN NaN NaN
## 11 10:00 NaN NaN 189.0000 NaN NaN 189.00000
## 12 11:00 NaN NaN NaN NaN NaN NaN
## 13 12:00 257.00 274.0 NaN 60.00000 NaN 197.00000
## 14 13:00 NaN NaN NaN NaN NaN NaN
## 15 14:00 313.00 NaN 153.0000 NaN NaN 233.00000
## 16 15:00 NaN 181.0 NaN NaN NaN 181.00000
## 17 16:00 91.20 NaN 66.0000 NaN NaN 78.60000
## 18 17:00 NaN NaN 66.0000 89.33333 NaN 77.66667
## 19 18:00 NaN 61.0 NaN NaN NaN 61.00000
## 20 19:00 NaN NaN NaN NaN NaN NaN
## 21 20:00 NaN NaN 236.6667 NaN NaN 236.66667
## 22 21:00 110.00 NaN 63.0000 NaN NaN 86.50000
## 23 22:00 NaN NaN NaN NaN NaN NaN
## 24 23:00 NaN 172.0 NaN NaN NaN 172.00000
## 25 mean 168.84 160.6 147.9630 130.06667 NaN 151.86741
#heatmap
heatMap(BGvalue_timeDaytable, hasTotals = TRUE,
margins = c(6,20), brks = seq(0,450,50),
brewerPallete = "RdBu")
Sensorvalue_timeDaytable
## time 2019-09-25 2019-09-26 2019-09-27 2019-09-28 2019-09-29 mean
## 1 00:00 115.16667 171.83333 NaN 106.16667 NaN 131.05556
## 2 01:00 115.33333 208.75000 NaN 88.41667 NaN 137.50000
## 3 02:00 135.00000 218.91667 NaN 82.41667 NaN 145.44444
## 4 03:00 149.66667 190.00000 NaN 112.41667 NaN 150.69444
## 5 04:00 151.41667 155.00000 NaN 174.16667 NaN 160.19444
## 6 05:00 142.75000 140.16667 NaN 209.83333 NaN 164.25000
## 7 06:00 152.91667 120.66667 NaN 242.16667 NaN 171.91667
## 8 07:00 129.83333 106.33333 NaN 218.25000 NaN 151.47222
## 9 08:00 69.83333 71.33333 NaN 211.83333 NaN 117.66667
## 10 09:00 92.41667 78.58333 NaN 233.25000 NaN 134.75000
## 11 10:00 168.75000 201.25000 186.00000 210.25000 NaN 191.56250
## 12 11:00 251.83333 266.00000 139.83333 146.16667 NaN 200.95833
## 13 12:00 238.41667 292.08333 77.58333 53.33333 NaN 165.35417
## 14 13:00 241.16667 279.00000 111.66667 162.25000 NaN 198.52083
## 15 14:00 286.75000 NaN 154.00000 213.33333 NaN 218.02778
## 16 15:00 220.16667 NaN 131.33333 189.25000 NaN 180.25000
## 17 16:00 70.50000 NaN 73.25000 117.41667 NaN 87.05556
## 18 17:00 63.25000 NaN 81.16667 64.25000 NaN 69.55556
## 19 18:00 133.25000 NaN 157.66667 112.66667 NaN 134.52778
## 20 19:00 112.00000 NaN 166.41667 127.00000 NaN 135.13889
## 21 20:00 102.41667 111.33333 218.00000 223.25000 112 153.40000
## 22 21:00 83.33333 107.58333 NaN 222.75000 NaN 137.88889
## 23 22:00 94.50000 124.58333 NaN 165.91667 NaN 128.33333
## 24 23:00 130.91667 137.16667 NaN 145.00000 NaN 137.69444
## 25 mean 143.81597 165.58796 136.08333 159.65625 112 143.42870
#heatmap
heatMap(Sensorvalue_timeDaytable, hasTotals = TRUE,
margins = c(6,20), brks = seq(0,450,50),
brewerPallete = "RdBu")
carbs_timeDaytable
## time 2019-09-25 2019-09-26 2019-09-27 2019-09-28 2019-09-29 max
## 1 00:00 NA NA 20 NA NA 20
## 2 01:00 NA NA NA 18 NA 18
## 3 02:00 NA NA NA NA NA NA
## 4 03:00 NA NA NA NA NA NA
## 5 04:00 NA NA NA NA NA NA
## 6 05:00 NA NA NA NA NA NA
## 7 06:00 NA NA 0 0 NA 0
## 8 07:00 17 20 10 NA NA 20
## 9 08:00 NA NA NA 20 NA 20
## 10 09:00 NA NA NA NA NA NA
## 11 10:00 10 NA NA NA NA 10
## 12 11:00 NA NA NA NA NA NA
## 13 12:00 0 30 NA NA NA 30
## 14 13:00 NA NA 20 25 NA 25
## 15 14:00 40 NA NA 10 NA 40
## 16 15:00 NA 10 NA 45 NA 45
## 17 16:00 NA NA NA NA NA NA
## 18 17:00 NA NA NA NA NA NA
## 19 18:00 30 NA 14 NA NA 30
## 20 19:00 NA NA NA 30 NA 30
## 21 20:00 NA NA 30 NA NA 30
## 22 21:00 NA 21 NA NA NA 21
## 23 22:00 28 NA 50 50 NA 50
## 24 23:00 NA 20 NA NA NA 20
## 25 max 40 30 50 50 NA 50
heatMap(carbs_timeDaytable, hasTotals = TRUE,
margins = c(6,15), brks = seq(0,100,10),
brewerPallete = "RdBu", textCol = "deeppink")
plotLine(allData, numberDays = numberDays, scatterOnly = TRUE,addSensor = FALSE,
plotSummary ="",
addBolusType = c("BWZ.Correction.Estimate..U."),
addSetting = c("basal"),
legendInset = -0.35, margins = c(10,4,3,15))
plotLine(allData, numberDays = numberDays, addSensor = TRUE,
colorPalleteDaily = "rainbow",plotSummary ="",
addBolus = FALSE,addSetting = "",
legendInset = -0.35, margins = c(10,4,3,15))
plotLine(allData, numberDays = numberDays, addSensor = FALSE,
colorPalleteDaily = "rainbow", plotSummary = "BG.Reading..mg.dL.",
addSetting = c("basal","corrFactor","carbRatio"), addBolus = FALSE,
legendInset = -0.35, margins = c(10,4,3,15))
plotLine(allData, numberDays = numberDays, addSensor = FALSE,
colorPalleteDaily = "rainbow",plotSummary ="Sensor.Glucose..mg.dL.",
addBolusType = c("Bolus.Volume.Delivered..U."),
addSetting = c("basal"),
legendInset = -0.35, margins = c(10,4,3,15))
plotLine(allData, numberDays = numberDays, addSensor = FALSE,
colorPalleteDaily = "rainbow",plotSummary ="Sensor.Glucose..mg.dL.",
addBolusType = "",addBolus = FALSE,
addSetting = c("basal","corrFactor","carbRatio"),
legendInset = -0.35, margins = c(10,4,3,15))
barPlot(allData, basal, corrFactor,carbRatio,
numberDays = numberDays, plotSummary = "BG.Reading..mg.dL.", sumFunc = "mean", stackedBar = "",
addBG = TRUE, addSetting = c("basal","corrFactor","carbRatio"),
legendInset = -0.35, margins = c(10,4,2,15))
barPlot(allData, basal, corrFactor,carbRatio,
numberDays = numberDays, plotSummary = "BG.Reading..mg.dL.", sumFunc = "mean", stackedBar = "BGrange",
addBG = FALSE, addSetting = c("basal","corrFactor","carbRatio"),
legendInset = -0.35, margins = c(10,4,2,15))
barPlot(allData, basal, corrFactor,carbRatio,
numberDays = numberDays, plotSummary = "BG.Reading..mg.dL.", sumFunc = "mean", stackedBar = "insulin",
addBG = FALSE, addSetting = c("corrFactor","carbRatio"),
legendInset = -0.35, margins = c(10,4,2,15))
{r, eval=TRUE}numberDays daysbarPlot(allData, basal, corrFactor,carbRatio,
filterCond = "data[data$BG.Reading..mg.dL.>150 & !is.na(data$BG.Reading..mg.dL.),]",
numberDays = numberDays, plotSummary = "BG.Reading..mg.dL.", sumFunc = "length", stackedBar = "",
addBG = TRUE, addSetting = c("basal","corrFactor","carbRatio"),
legendInset = -0.35, margins = c(10,4,2,15))
barPlot(allData, basal, corrFactor,carbRatio,
filterCond = "data[data$BG.Reading..mg.dL.<80 & !is.na(data$BG.Reading..mg.dL.),]",
numberDays = numberDays, plotSummary = "BG.Reading..mg.dL.", sumFunc = "length", stackedBar = "",
addBG = TRUE, addSetting = c("basal","corrFactor","carbRatio"),
legendInset = -0.35, margins = c(10,4,2,15))
{r, eval=TRUE}numberDays days#boxplots
boxPlot(allData,basal, corrFactor,carbRatio, numberDays = numberDays, filterCond = "",
plotSummary = "BWZ.Carb.Input..grams.",
addSetting = "",
legendInset = -0.3, margins = c(10,4,2,15))
boxPlot(allData,basal, corrFactor,carbRatio, numberDays = numberDays, filterCond = "",
plotSummary = "BG.Reading..mg.dL.",
addSetting ="basal",
legendInset = -0.3, margins = c(10,4,2,15))
plotLine_ly(allData, scatterOnly = FALSE, pointSize = 10,
numberDays = 5, startDate = "2019-09-08", endDate = "2019-09-08",
startTime = "00:00", endTime = "23:00",
colorPalleteDaily = "rainbow",
addSensor = FALSE, addBG = TRUE, settingOverlay = FALSE,
addBolusType = "",
plotSummary = "Sensor.Glucose..mg.dL.",
addSetting =c("basal","carbRatio","corrFactor"),
addBarSub = FALSE,addPercentType = "Sensor.Glucose..mg.dL.",
filterCond = "",
legendInset = -0.2)
plotLine_ly(allData, scatterOnly = FALSE, pointSize = 10,
numberDays = 5, startDate = "2019-09-08", endDate = "2019-09-08",
startTime = "00:00", endTime = "23:00",
colorPalleteDaily = "rainbow",
addSensor = FALSE, addBG = TRUE, settingOverlay = FALSE,
addBolusType = "",
plotSummary = "Sensor.Glucose..mg.dL.",
addSetting =c("basal","carbRatio","corrFactor"),
addBarSub = FALSE,
filterCond = "",
legendInset = -0.2)
plotLine_ly(allData, scatterOnly = FALSE, pointSize = 10,
numberDays = 5, startDate = "2019-09-08", endDate = "2019-09-08",
startTime = "00:00", endTime = "23:00",
colorPalleteDaily = "rainbow",
addSensor = FALSE, addBG = TRUE, settingOverlay = FALSE,
addBolusType = "",
plotSummary = "Sensor.Glucose..mg.dL.",
addSetting ="",
addBarSub = TRUE,
filterCond = "",
legendInset = -0.2)
plotLine_ly(allData, scatterOnly = FALSE, pointSize = 10,
numberDays = 5, startDate = "2019-09-08", endDate = "2019-09-08",
startTime = "00:00", endTime = "23:00",
colorPalleteDaily = "rainbow",
addSensor = FALSE, addBG = TRUE, settingOverlay = FALSE,
addBolusType = "",
plotSummary = "Sensor.Glucose..mg.dL.",
addSetting =c("basal","carbRatio","corrFactor"),
addBarSub = TRUE,
filterCond = "",
legendInset = -0.2)
barSubPlot_ly(p = NA, data = allData, barSubPlot = FALSE,ayCarb = NA,
addBarSub = FALSE,basal,
numberDays = 5, filterCond = "data[data$BG.Reading..mg.dL.>150 & !is.na(data$BG.Reading..mg.dL.),]",
startDate = NA, endDate = NA,
startTime = "00:00", endTime = "23:00",
plotSummary ="BG.Reading..mg.dL.", sumFunc = "length", stackedBar = "",
addBG = FALSE, uniqueDT = TRUE,replaceNAs = FALSE,
addSetting = c("basal","corrFactor","carbRatio"),settingOverlay = FALSE,percentSetting = 30,
legendInset = -0.2)
barSubPlot_ly(p = NA, data = allData, barSubPlot = FALSE,ayCarb = NA,
addBarSub = FALSE,basal,
numberDays = 5, filterCond = "data[data$BG.Reading..mg.dL.<80 & !is.na(data$BG.Reading..mg.dL.),]",
startDate = NA, endDate = NA,
startTime = "00:00", endTime = "23:00",
plotSummary ="BG.Reading..mg.dL.", sumFunc = "length", stackedBar = "",
addBG = FALSE, uniqueDT = TRUE,replaceNAs = FALSE,
addSetting = c("basal","corrFactor","carbRatio"),settingOverlay = FALSE,percentSetting = 30,
legendInset = -0.2)
barSubPlot_ly(p = NA, data = allData, barSubPlot = FALSE,ayCarb = NA,
addBarSub = FALSE,basal,
numberDays = 5, filterCond = "",
startDate = NA, endDate = NA,
startTime = "00:00", endTime = "23:00",
plotSummary ="", sumFunc = "", stackedBar = "insulin",
addBG = FALSE, uniqueDT = TRUE,replaceNAs = TRUE,
addSetting = c("basal","corrFactor","carbRatio"),settingOverlay = FALSE,percentSetting = 30,
legendInset = -0.2)
barSubPlot_ly(p = NA, data = allData, barSubPlot = FALSE,ayCarb = NA,
addBarSub = FALSE,basal,
numberDays = 5, filterCond = "",
startDate = NA, endDate = NA,
startTime = "00:00", endTime = "23:00",
plotSummary ="BG.Reading..mg.dL.", sumFunc = "length", stackedBar = "BG",
addBG = FALSE, uniqueDT = TRUE,replaceNAs = FALSE,ignoreNAs = TRUE,
addSetting = c("basal","corrFactor","carbRatio"),settingOverlay = FALSE,percentSetting = 30,
legendInset = -0.2)